Hybrid Renewable Energy System Research Articles

Future perspectives on new innovative technologies comparison against hybrid renewable energy systems

The increase in the dispatchable amount of renewable energy and rural access to the point is proposed. The fuel is used to generate power and electrical energy for the machine. This causes the electricity to manage the single connection point to analyze the hybrid generations. Improving this hybrid generator of renewable power resources can be enabled for the analysis. Photovoltaic power sources have been introduced for converting the power loads and the dumps. The vehicle energy power management technique and the renewable energy system have been used for the analysis. This study shows how vehicle and renewable energy management can help develop geothermal against hydrothermal vents. Hydropower and vehicles can enable bioethanol for vehicle biodiesel. This study allows for the analysis of hydrothermal and biodiesel. In this study, the power of the energy enables the hybrid system, and the combination of the power generator to access the vehicle is proposed.

AI-enabled metaheuristic optimization for predictive management of renewable energy production in smart grids

The integration of renewable energy sources into smart grids offers a promising solution for building sustainable and reliable energy systems. However, optimizing hybrid renewable energy systems remains a crucial area of research. The study presents a comprehensive approach combining artificial intelligence algorithm techniques with metaheuristic optimization algorithms for anticipating and managing renewable energy sources in smart grid environments. With precision, recall, and accuracy scores of 0.92, 0.93, and 0.92, respectively, the proposed Hybrid LSTM-RL model beats current algorithms in correctly forecasting energy demand patterns. With an accuracy of 0.91 for various load balancing measures, the RL-SA algorithm efficiently measures load balancing. With mean squared error (MSE), mean absolute error (MAE), R-squared score, root mean square error (RMSE), and mean absolute percentage error (MAPE) values of 345.12, 15.07, 0.78, 18.57, and 7.83, respectively, the CNN-PSO algorithm also turns out to be the most successful at forecasting the generation of renewable energy. These discoveries help hybrid renewable energy systems in smart grid settings advance, enabling effective, dependable, and economical energy production and distribution. The suggested solution also has the potential to be used in rural and off-grid settings. Overall, this research offers a useful method for maximizing the production of renewable energy and acts as a spark for additional studies into energy management systems.

Energy, exergy, exergoeconomic and exergoenvironmental analyses of a hybrid renewable energy system with hydrogen fuel cells

In this study, the energy, exergy, exergoeconomic and exergoenvironmental (4E) analyses of a cogeneration system that combines photovoltaic thermal panels (PV/T), evacuated tube solar collectors, an organic Rankine cycle (ORC) and energy storage systems are performed. The cogeneration model is built to meet the load demand of independent houses in remote areas and avoids excessive consumption of traditional energy and environmental pollution. Here, the exergoenvironmental analysis adopts the Eco-indicator-99 method and the all life cycle assessment method is used to calculate the environmental impact of each component. Two comparative studies are conducted to the 4E analyses. The first one compares the comprehensive performance of the battery storage and hydrogen production for energy storage. The results indicate that the cogeneration system using both batteries and hydrogen production for energy storage has the best overall performance. According the exergoeconomic and exergoenvironmental analyses, its environmental impact is 23.6% lower than the cogeneration system using batteries alone and the PV/T can be fully utilized. In addition, the total cost rate is 6.2% lower than the cogeneration system using hydrogen production alone. The second case investigates the effect of adding the evacuated tube solar collectors between the PV/T and ORC on the cogeneration system. The analysis results demonstrate that the evacuated tube solar collectors can increase the heat source temperature of the ORC to increase the power generation of the ORC by 37.14%; however, the total cost rate of the cogeneration system increases by 3.7% and the environmental impact rate increases by 19.8%.

Estimation of Energy Consumption for Concentrate Process of Tungsten Ore towards the Integration of Renewable Energy Sources in Mongolia

It is important to estimate the energy required in ore processing to select the most affordable and efficient energy system for the integration of renewable resources into the mining industry. In the present work, the energy consumption for the concentrate of tungsten ore in Mongolia was theoretically predicted based on operational variations (particle size and the hardness of the tungsten ore) and different equipment. The energy was in the range from 0.48 to 1.32 kWh/t for the crushing stage, and a cone crusher was more suitable than a jaw crusher due to the particle size of feed material and product. The required energy in the grinding stage was from 6.22 to 11.88 kWh/t using a SAG mill or from 3.04 to 7.39 kWh/t using a ball mill. The further separation by a flotation consumed 4.83 kWh/t or by a shaking table consumed 1.29 kWh/t. The maximum energy consumption per hour for the whole process was estimated to be 2–3 MW, which was better to integrate with a hybrid renewable energy system. The sizing method Power Pinch Analysis was used to estimate the electric supply based on the combination of wind, biomass and solar resources, which was sufficient for the demand from the predicted range of energy.

Coupled thermo-electrical dispatch strategy with AI forecasting for optimal sizing of grid-connected hybrid renewable energy systems

In multi-energy systems the full utilisation of the generated energy is a challenge. Integrating heat and electricity supply at the system level design could provide an opportunity to address this challenge. In this paper we introduce and examine two coupled thermal-electrical dispatch strategies for grid-connected hybrid multi-energy systems supplying electrical and thermal demand loads. The dispatch strategy employs forecasting of energy resources and demand loads to prioritise supplying the thermal load in times of renewable surplus. Four forecasting algorithms, namely, baseline forecast, Facebook Prophet (FBP), Neural Prophet (NP), and Long Short-Term Memory model (LSTM) are implemented and used to generate annual forecast data for solar irradiance, wind speed, and thermal and electrical demand loads. To integrate forecast data within the dispatch strategy, new parameters are proposed to quantify the expected available energy within the forecast time horizon. A building complex for the Department of Education in the UK is used for conducting a system design case study. A genetic algorithm-based multi-objective optimisation with the levelised costs of electricity and heat as two objectives is conducted. The results show that the proposed dispatch algorithm produces systems with reduced levelised costs compared to the base case of using utility gas and electricity. Forecasting is particularly useful in reducing cost of heat, as it can prioritise supplying the thermal load in times of renewable surplus. LSTM proved to be the most accurate forecasting algorithm for this case, where the data has strong seasonality and trends. The main contribution of this work is to propose and demonstrate the effectiveness of tightly coupling thermo-electrical dispatch algorithms of HRES from the design stage, and how to effectively integrate forecast data within such algorithms.

Design Optimization and Analysis of on-Grid Hybrid Renewable Energy System for Audio-Visual Chain

Rapid advancement of various renewable energies (especially wind and solar energies) as well as energy storage technologies dramatically changes the current energy configuration including the television buildings. In this paper, a micro-grid with high penetration of clean energy systems has been designed for an audio-visual chain. The design and performance optimization of on-grid hybrid renewable energy system using hybrid optimization software is developed and analyzed. The micro-grid design containing photovoltaic panels, wind turbines and storage batteries connected to the grid with a backup diesel generator. The technical and economic advantages of a micro-grid based on clean energy sources for an audio-visual chain located in Tunisia is presented to improve the performance of industrial buildings by providing a green environment with alternative energy sources to meet the high energy demand. This analysis is accomplished by studying solar and wind energy potentials and by aggregating data from various sources. The system was analyzed using HOMER software, which simulate and optimize the proposed micro-grid to a specific demand (audio-visual production chain) with a sensitive/normal loads and energy sources. For the economic analysis, the net present cost was used as objective function in the optimization process. The obtained results show that, in the selected configuration of micro-grid, 49.4% of all energy is supplied by renewable sources with a Total Net Present Cost of $5.02 M under a minimum COE of $0.0609/kWh.

Modelling and multi-objective optimisation of sustainable solar-biomass-based hydrogen and electricity co-supply hub using metaheuristic-TOPSIS approach

The utilisation of biomass and solar energy for green hydrogen production offers potential benefits in reducing carbon emissions and enhancing energy security, aligning with global sustainability efforts. However, research is still limited in optimising hybrid renewable energy systems that leverage biomass and solar energy for a balanced co-supply of hydrogen and electricity in industrial settings. In addition, the identification of optimal capacity configurations for these systems can be challenging, due to supply–demand variations and conflicting design objectives. For the first time, we demonstrate the use of a two-stage multi-objective metaheuristic-Technique for Order of Preference by Similarity to Ideal Solutions (TOPSIS) method for the design of a solar-biomass-based hydrogen and electricity co-supply hub (HECH), based on the consideration of economic, supply stability, and waste energy generation aspects. Through a proposed case study in Felda Taib Andak, Malaysia, the best-compromised solution for capacity setup is successfully determined. Among the metaheuristics screened, the TOPSIS-assisted multi-objective mayfly algorithm (MMA) provides the most preferred capacity arrangement, minimising the total annualised cost (TAC) to USD 9.43 mil./yr and hydrogen and power supply probabilities (LHSP and LPSP) to 0.188 and 0.328, respectively. The MMA-TOPSIS approach also reduces the potential energy waste probability (PEWP) of HECH down to 0.09. The study also discusses the feasibility of battery and hydrogen storage during critical periods such as low and high biomass feed supplies. Overall, the outcomes of this research offer guidance to the engineers in optimising HECH designs, which sets the groundwork for low-carbon energy development in biomass-related industrial ecosystems.

Optimal Design and Operation of Hybrid Renewable Energy Systems for Oakland University

This research paper presents a comprehensive study on the optimal planning and design of hybrid renewable energy systems for microgrid (MG) applications at Oakland University. The HOMER Pro platform analyzes the technical, economic, and environmental aspects of integrating renewable energy technologies. The research also focuses on the importance of addressing unmet load in the MG system design to ensure the university’s electricity demand is always met. By optimizing the integration of various renewable energy technologies, such as solar photovoltaic (PV), energy storage system (ESS), combined heat and power (CHP), and wind turbine energy (WT), the study aims to fulfill the energy requirements while reducing reliance on traditional grid sources and achieving significant reductions in greenhouse gas emissions. The proposed MG configurations are designed to be scalable and flexible, accommodating future expansions, load demands changes, and technological advancements without costly modifications or disruptions. By conducting a comprehensive analysis of technical, economic, and environmental factors and addressing unmet load, this research contributes to advancing renewable energy integration within MG systems. It offers a complete guide for Oakland University and other institutions to effectively plan, design, and implement hybrid renewable energy solutions, fostering a greener and more resilient campus environment. The findings demonstrate the potential for cost-effective and sustainable energy solutions, providing valuable guidance for Oakland University’s search for energy resilience and environmental surveillance, which has a total peak load of 9.958 MW. The HOMER simulation results indicate that utilizing all renewable resources, the estimated net present cost (NPC) is a minimum of USD 30 M, with a levelized energy cost (LCOE) of 0.00274 USD/kWh. In addition, the minimum desired load will be unmetered on some days in September.

Operational strategy and capacity optimization of standalone solar-wind-biomass-fuel cell energy system using hybrid LF-SSA algorithms

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system.

An Analysis of Hybrid Renewable Energy System Using HOMER Pro: A Case Study in Sungai Tiang Camp, Perak

An extraordinary worldwide shift is occurring in the twenty-first century, as people increasingly turn to renewable energy sources. However, hybrid renewable energy system (HRES) development in rural regions is technically difficult and financially expensive to provide energy access. Due to the various components necessary to produce a hybrid system, its construction is often costly. As the remote areas depend on unsustainable diesel-fuelled generators, they have greater operational expenses than non-remote areas due to the higher cost of diesel and the longer distances needed to transport the fuel. This work focuses on modelling a hybrid renewable energy system that is economically sustainable, environmentally friendly and technical consideration is taken into the design requirements. The energy cost ($/kWh) and lifecycle emission CO2 (kg/year) are considered as economic and environmental indicators, respectively. In addition, a sensitivity analysis for varied diesel fuel price ($/L) and PV capital cost of the HRES is performed to achieve a more feasible configuration. To obtain a system that can fulfil demand while meeting specific technical requirements, three configurations are evaluated: 1) standalone diesel generators, 2) hybrid PV-Diesel without battery and 3) hybrid PV-Diesel with battery. This study proposed system 3 as the best system architecture due to the lowest value of COE of 0.258$/kWh and NPC of $22,130. A solar photovoltaic (PV) and lead acid (LA) battery-based hybrid renewable energy system is suggested to fulfil the camp facility load demand of 14.92kWh/day in a rural area of Sungai Tiang, Perak. Sensitivity analysis findings show that LCOE and NPC values are substantially responsive to fuel price and PV capital cost. Integrated solar and battery technologies can enhance the economic performance (e.g., NPC, COE), environmental performance (e.g., carbon dioxide emissions), and technical performance (e.g., fuel consumption) of a renewable energy system.

Comparative assessment of multi-objective optimization of hybrid energy storage system considering grid balancing

With the accelerated transition towards affordable and clean energy sources, the energy sector is undergoing a structural transformation that has resulted in a further increase in the complexity of energy system planning with rapid changes in techno-economic, environmental, reliability and social constraints. This signifies the consideration of purpose-driven multi-objective functions depending upon the functionality and applicability of the model. However, most of the studies adopt conventional bi-objective optimization either involving techno-economic, reliability and grid balancing parameters but there is a lack of comparative assessment of multi-objective optimization sizing for grid-interactive hybrid renewable energy system (HRES) consisting of short and long-term, battery and pumped hydro storage (PHS), energy storage systems (ESS). This study presents a comparative multi-objective framework to assess bi- and tri-objective function sizing techniques under grid balancing and non-balancing modes, to understand the scope and adaptivity of the modeling process for large-scale grid-interactive HRES. The analysis of results shows that the non-balancing mode underestimates the cost of energy (COE) by 18–30% compared to the grid balancing mode due to smaller decision variable space while long-term ESS dominance is vital for the reduction of grid burden compared to short-term ESS. In terms of configuration, a hybrid ESS system, 0.22 MWh battery, 18.1 MWh PHS, and 5.4 MW PV capacity, is the best optimal configuration in grid balancing mode with the COE, EEI and EII equal to 0.09 $/kWh, 7.5% and 10.5% respectively, whereas higher grid energy mismatch is induced by non-balancing mode with the overestimation of EEI and EII indexes up to 30% and 33% respectively. The environmental analysis shows that the carbon emissions avoided (CEA) are underestimated by 59.1% with the non-consideration of grid balancing. This signifies that the adaptive optimization model improves the design and planning process of grid-interactive HRES by capturing larger uncertainties related to COE, grid balancing, and CEA with changes in the system and ESS sizing. Overall, this analysis provides a purpose-driven perspective to energy modelers and policymakers for the energy system modeling process of grid-interactive HRES.

Design and implementation of a cost-efficient clamping capacitor boost converter for a hybrid renewable energy system for increased gain to fulfil demands

Power generation plants are built in rural areas to meet the power demands and empower the financial status. The existing method of electrical power generation is difficult to meet the growing population as they are turning to hybrid renewable energy systems to meet the increasing demand. They were also not focused on power saving and flow with reduced power loss. The power generated from hybrid renewable energy systems is distributed to rural areas through a DC-DC converter. The DC-DC converter converts the Hybrid Renewable Energy System (HRE) output into a high DC voltage transmitted in a bus. The proposed HRE system consists of solar and wind plants in the network. So, for transferring, saving, and utilizing the power generated from the hybrid renewable energy system, a cost-efficient clamping capacitor boost converter (CCBC) with increased voltage gain is proposed. The CCBC has a clamping capacitor in-built with 2-diodes and 2-capacitors. The voltage gain produced using the proposed CCBC is doubled with the conventional converters. There is no high range of power spikes in the converter's capacitor. This paper explains the architecture and the complete functionality of the CCBC with the simulation results in detail. The simulation results conclude that the proposed CCBC provides cost-efficient high voltage gain converters for HRE systems, providing more than 500 W, which fulfills the demand of a single rural area.

Modelling & Simulation of a Hybrid Microgrid System Using Renewable Energy Sources

Abstract: The rapid growth of industries and load consumption increases the energy demand that needs to fulfilling this energy demand can be obtained from various alternative sources has much importance. The novel hybrid renewable energy system consists of different sources such as the Photovoltaic (PV) system, Wind Energy system (PMSG), Fuel Cell, and the AC source are implemented as energy sources.

Techno-Economic Analysis and Optimization of Hybrid Renewable Energy System with Energy Storage under Two Operational Modes

Access to cheap, clean energy has a significant impact on a country’s ability to develop sustainably. Fossil fuels have a major impact on global warming and are currently becoming less and less profitable when used to generate power. In order to replace the diesel generators that are connected to the university of Debre Markos’ electrical distribution network with hybrid renewable energy sources, this study presents optimization and techno-economic feasibility analyses of proposed hybrid renewable systems and their overall cost impact in stand-alone and grid-connected modes of operation. Metaheuristic optimization techniques such as enhanced whale optimization algorithm (EWOA), whale optimization algorithm (WOA), and African vultures’ optimization algorithm (AVOA) are used for the optimal sizing of the hybrid renewable energy sources according to financial and reliability evaluation parameters. After developing a MATLAB program to size hybrid systems, the total current cost (TCC) was calculated using the aforementioned metaheuristic optimization techniques (i.e., EWOA, WOA, and AVOA). In the grid-connected mode of operation, the TCC was 4.507 × 106 EUR, 4.515 × 106 EUR, and 4.538 × 106 EUR, respectively, whereas in stand-alone mode, the TCC was 4.817 × 106 EUR, 4.868 × 106 EUR, and 4.885 × 106 EUR, respectively. In the grid-connected mode of operation, EWOA outcomes lowered the TCC by 0.18% using WOA and 0.69% using AVOA, and by 1.05% using WOA and 1.39% using AVOA in stand-alone operational mode. In addition, when compared with different financial evaluation parameters such as net present cost (NPC) (EUR), cost of energy (COE) (EUR/kWh), and levelized cost of energy (LCOE) (EUR/kWh), and reliability parameters such as expected energy not supplied (EENS), loss of power supply probability (LPSP), reliability index (IR), loss of load probability (LOLP), and loss of load expectation (LOLE), EWOA efficiently reduced the overall current cost while fulfilling the constraints imposed by the objective function. According to the result comparison, EWOA outperformed the competition in terms of total current costs with reliability improvements.

Modeling, Simulation, and Experimental Analysis of a Photovoltaic and Biogas Hybrid Renewable Energy System for Electrification of Rural Community

This research is a numerical study, with simulation and experimental investigation of a novel photovoltaic and biogas hybrid renewable energy system. PVSYST simulation software is used to evaluate the energy generation of photovoltaic (PV) systems installed at optimum tilt angle and interrow spacing, as well as measure the performance ratio and system losses. The results obtained from simulations show that annual energy production from designed PV system is 16 654.80 kWh year−1 and its annual specific energy production is 1556.5 kWh kWp year−1. The average annual performance ratio is about 84.3%, normalized array production is 3.23 kWh kWp day−1, normalized system losses are 0.07 kWh kWp day−1, and normalized system production is 3.16 kWh kWp day−1. With SuperPro Designer software, a model is developed for simulating anaerobic digestion for treating animal manure to produce biogas. The simulation yields 88.13% of CH4 and 6.49% of CO2. The performance of the installed experimental setup is examined for 30 d. The maximum load demand of all houses is 46.902 kWh, whereas maximum energy produced by a hybrid PV/biogas system is 61.06 kWh. The payback period for a hybrid photovoltaic/biogas system is estimated to be 4.47 years and levelized cost of energy is 0.0186 USD kWh−1. The hybrid PV/biogas system results in net CO2 mitigation of 20.45 tCO2(e).

Islanded green energy system optimal analysis using PV, wind, biomass, and battery resources with various economic criteria

The main goal of this paper is to design an efficient renewable energy system that meets the required electricity demands. Consequently, it is essential to find the most cost-effective hybrid system that can reduce energy costs and provide access to the required electricity generation. An international school in New Administrative Capital in New Cairo, Egypt was chosen as a study area for the proposed system. Solar, wind, and biomass resources are abundant at the chosen location throughout the year. Using the HOMER (hybrid optimization model for electric renewables) software, eight distinct models of renewable energy hybrid systems were designed, simulated, and optimized to meet the required load in this study. For wind and solar resources, the National Aeronautics and Space Administration (NASA) provided the input data; for biomass resources, real-time field data were used for the selected study site. In this study, lithium-ion and lead acid batteries were used to choose the most cost-effective option. The hybrid power system's PV, wind, and biomass generators were utilized to meet the load demand. The overabundance of energy requests was utilized to charge the battery banks as required when accessible to cover the load requirements during times of low energy production.

A licensing plan for coupling nuclear–renewable hybrid energy systems

South Africa committed to reducing greenhouse gas emissions by 34% below "Business As Usual" levels by 2020 and 42% by 2025 at the Copenhagen climate change conference. However, global energy demand was projected to rise due to population and industrial growth, with energy usage expected to increase by 13% through 2040. In South Africa, a steady increase in electricity demand prompted the government to implement a new growth path (NGP), which prioritized job creation in all economic policies, including energy. To address the growing energy demand, an alternative energy source for combined heat and power was necessary, particularly for synthetic fuel production. The coupling of a high temperature reactor (HTR) with a chemical process plant could improve carbon and thermal efficiency, as seen in international organizations like the ARCHER (Advanced High-Temperature Reactors for Cogeneration of Heat and Electricity R&D) project. HTRs are still in their conceptual stages andaresuitable candidate forcouplingto an energy-intensiveindustrythat require process heat with sufficiently hightemperatures,with potential uses for NRHES (Nuclear-Renewable Hybrid Energy Systems). The South African team aimed to model the SASOL process, assess its financial viability, and develop a licensing plan.

Design and performance assessment of a pumped hydro power energy storage connected to a hybrid system of photovoltaics and wind turbines

Worldwide, the overdependence on conventional power plants for electricity generation has been one of the most significant economic and environmental challenges. Renewable energy sources have become the most viable option to overcoming this issue. Recently, a hybrid renewable energy system consisting of wind turbines and photovoltaics combined with a pumped hydroelectric energy storage system has received considerable interest. However, neglecting crucial parameters, such as head losses and evaporation rate, might reduce the accuracy of the total simulation performance, resulting in an underestimation of the correct size of each component. This study investigates this issue by proposing a robust approach with a strategy to establish the ideal pipe design through an in-depth techno-economic assessment. A comparative analysis between two different scenarios in which one considers head loss and the other does not is carried out. A wide range of proposed system configurations has been thoroughly investigated. The essential performance indicators employed for designing the proposed system are the renewable energy fraction and the loss of renewable energy, and the results reveal that these two indicators have improved by approximately 8.6% and 3%, respectively. The most significant annual variation between the two scenarios regarding the total demand satisfied by the proposed system and the amount of renewable energy loss is 218.23 GWh and 89.39 GWh, respectively. The pipe efficiency at the pumping and generating modes, which is determined through a sensitivity analysis, ranges between 91-99% and 76–95%, respectively. These findings could assist designers in making initial assumptions about such parameters with reasonable confidence.

Hydrogen as a Renewable Energy Carrier in a Hybrid Configuration of Distributed Energy Systems: Bibliometric Mapping of Current Knowledge and Strategies

Storing energy in hydrogen deposits balances the operation of energy systems and is an effective tool in the process of energy transformation towards achieving Sustainable Development Goals. To assess the validity of its use as an alternative renewable energy carrier in dispersed energy systems of hybrid configuration, a comprehensive review of scientific literature was conducted in this study, based on bibliometric analysis. The bibliographic database used in the study was the international Web of Science database. This review contributes to a better understanding of the characteristics of the selected research area. The evolution of research trends implemented in the design of energy systems associated with hydrogen technologies is revealed, clearly indicating that it is a developing field. In recent years, there has been an increase in the number of publications, although the territorial range of research (mainly simulation) conducted in the domain does not include areas with the most favourable infrastructural conditions. The analysis reveals weak cooperation between South American, African, East Asian, and Oceanic countries. In the light of earlier, thematically similar literature reviews, several research gaps are also identified and proposals for future research are presented. They concern, in particular, the parallel implementation and optimization of the operation of hydrogen (HRES—Hybrid Renewable Energy System and HESS—Hybrid Energy Storage System) solutions in terms of economics, ecology, lifespan, and work efficiency, as well as their feasibility analysis. With the support of other researchers and those involved in the subject matter, this review may contribute to the further development of hybrid hydrogen systems in terms of increasing competitiveness and promoting the implementation of these technologies.

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

AbstractThe constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices.